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But the benign examples were just as interesting. In one test of locomotion, a simulated robot was programmed to travel forward as quickly as possible. But instead of building legs and walking, it built itself into a tall tower and fell forward. How is growing tall and falling on your face anything like walking? Well, both cover a horizontal distance pretty quickly. And the AI took its task very, very literally.

According to Janelle Shane, a research scientist who publishes a website about artificial intelligence, there is an eerie genius to this forward-falling strategy. After I had posted [this paper] online, I heard from some biologists who said, Oh yeah, wheat uses this strategy to propagate! she told me. At the end of each season, these tall stalks of wheat fall over, and their seeds land just a little bit farther from where the wheat stalk heads started.

From the perspective of the computer programmer, the AI failed to walk. But from the perspective of the AI, it rapidly mutated in a simulated environment to discover something which had taken wheat stalks millions of years to learn: Why walk, when you can just fall? A relatable sentiment.

The stories in this paper are not just evidence of the dim-wittedness of artificial intelligence. In fact, they are evidence of the opposite: A divergent intelligence that mimics biology. These anecdotes thus serve as evidence that evolution, whether biological or computational, is inherently creative and should routinely be expected to surprise, delight, and even outwit us, the lead authors write in the conclusion. Sometimes, a machine is more clever than its makers.

This is not to say that AI displays what psychologists would call human creativity. These machines cannot turn themselves on, or become self-motivated, or ask alternate questions, or even explain their discoveries. Without consciousness or comprehension, a creature cannot be truly creative.

But if AI, and machine learning in particular, does not think as a person does, perhaps its more accurate to say it evolves, as an organism can. Consider the familiar two-step of evolution. With mutation, genes diverge from their preexisting structure. With natural selection, organisms converge on the mutation best adapted to their environment. Thus, evolutionary biology displays a divergent and convergent intelligence that is a far better metaphor for to the process of machine learning, like generative design, than the tangle of human thought.

AI might not be smart in a human sense of the word. But it has already shown that it can perform an eerie simulation of evolution. And that is a spooky kind of genius.

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